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import json
import datasets
_DESCRIPTION = """\
Dataset com imagens de comprovantes de pagamento e notas ficais no Brasil.
"""
_URL_JSON="https://huggingface.co/datasets/gugaime/dokki-pagamentos/raw/main/train.jsonl"
_URL = "https://huggingface.co/datasets/gugaime/dokki-pagamentos/resolve/main/images.zip"
class Dokki(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"image": datasets.Image(),
"id": datasets.Value("string"),
"ner_tags": datasets.Sequence(datasets.ClassLabel(num_classes=5, names=['O', 'cnpj', 'cpf', 'data', 'total'])),
"tokens": datasets.Sequence(datasets.Value("string")),
"bboxes": datasets.Sequence(datasets.Sequence(datasets.Value("int64")))
}
),
# No default supervised_keys (as we have to pass both question
# and context as input).
supervised_keys=None,
homepage="",
)
def _split_generators(self, dl_manager):
path = dl_manager.download(_URL)
image_iters = dl_manager.iter_archive(path)
json_path = dl_manager.download(_URL_JSON)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"images": image_iters, "json_path": json_path})
]
def _generate_examples(self, images, json_path):
idx = 0
imageMap = {}
for filepath, image in images:
imageMap[filepath] = {"image": {"path": filepath, "bytes": image.read()}}
with open(json_path, 'r') as f:
for line in f:
data = json.loads(line)
path = data["imagePath"]
row=imageMap[path]
row["id"]=data["id"]
row["ner_tags"]=data["labels"]
row["tokens"]=data["texts"]
bboxex = [ [bbox[0][0], bbox[0][1], bbox[1][0], bbox[1][1]] for bbox in data["bboxes"]]
row["bboxes"]=bboxex
yield idx, row
idx += 1 |